As a general and rigid mathematical tool, wavelet theory has found many applications and is
constantly developing. This article reviews the development history of wavelet theory, from�…

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies�…

This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG)�…

This second edition of The Illustrated Wavelet Transform Handbook: Introductory Theory and
Applications in Science, Engineering, Medicine and Finance has been fully updated and�…

Non-stationary time series (TS) analysis has gained an explosive interest over the recent
decades in different applied sciences. In fact, several decomposition methods were�…

This study proposes a new model which is fully specified for automated seizure onset
detection and seizure onset prediction based on electroencephalography (EEG)�…

In this study, three popular signal processing techniques (Empirical Mode Decomposition,
Discrete Wavelet Transform, and Wavelet Packet Decomposition) were investigated for the�…

Technically, a feature represents a distinguishing property, a recognizable measurement,
and a functional component obtained from a section of a pattern. Extracted features are�…

The last 15 years have seen an explosion of interest in wavelets with applications in fields
such as image compression, turbulence, human vision, radar and earthquake prediction�…

Wheel defects on railway wagons have been identified as an important source of damage to
the railway infrastructure and rolling stock. They also cause noise and vibration emissions�…